CN113743638A - Method and equipment for predicting gas concentration of refrigerator and refrigerator - Google Patents
Method and equipment for predicting gas concentration of refrigerator and refrigerator Download PDFInfo
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Abstract
The invention discloses a method and equipment for predicting gas concentration by a refrigerator and the refrigerator, wherein the method comprises the following steps: acquiring the gas concentration Ct of a kitchen; when the gas concentration Ct of the kitchen reaches a preset lower limit value Ct0, obtaining a linear regression equation Ct ═ w t + b of the gas concentration rise according to the gas concentration rise data of the Ct in a preset time period; and calculating the early warning time t1 when the gas concentration reaches the early warning value Ct1 according to the linear regression equation and the time t0 when the gas concentration reaches the lower limit value Ct0, and sending the early warning time t1 to a user. Compared with the prior art, the method for predicting the gas concentration of the refrigerator obtains the gas concentration rising data in the preset time period after the gas is determined to start to leak, obtains the linear regression equation of the gas concentration rising, accordingly realizes prediction of the predicted gas concentration, sends related prediction information to a user, prevents further leakage of the gas concentration, and reduces harm of the gas to a human body.
Description
Technical Field
The invention relates to the field of household appliance control, in particular to a method and equipment for predicting gas concentration of a refrigerator and the refrigerator.
Background
The coal gas enters ordinary families as a main fuel for heating and cooking, and although the coal gas is clean, sanitary and environment-friendly, the coal gas is easy to leak and brings great potential safety hazards to people without attention because the coal gas is toxic.
The existing gas leakage detection generally gives an alarm when the gas concentration reaches a certain value, but the gas in the air still has an influence on a human body at the moment, and how to predict the gas concentration and inform a user when the gas concentration is found to be abnormal at first is needed, so that the gas concentration is prevented from being further leaked, the influence of the gas on the human body is reduced, and the problem to be solved is urgently needed.
Disclosure of Invention
The invention aims to provide a method and equipment for predicting gas concentration of a refrigerator and the refrigerator.
In order to achieve one of the above objects, an embodiment of the present invention provides a method for predicting a gas concentration in a refrigerator, the method including:
acquiring the gas concentration Ct of a kitchen;
when the gas concentration Ct of the kitchen reaches a preset lower limit value Ct0, obtaining a linear regression equation Ct ═ w t + b of the gas concentration rise according to the gas concentration rise data of the Ct in a preset time period;
and calculating the early warning time t1 when the gas concentration reaches the early warning value Ct1 according to the linear regression equation and the time t0 when the gas concentration reaches the lower limit value Ct0, and sending the early warning time t1 to a user.
As a further improvement of an embodiment of the present invention, the "obtaining a linear regression equation Ct ═ w × t + b according to the rising data of the gas concentration Ct in the predetermined time period" specifically includes:
uniformly acquiring N rising data C1-Cn of the gas concentration in the preset time period;
calculating a regression parameter w:
and substituting the C1-Cn and w into the linear regression equation to obtain an initial value b of the coal gas concentration.
As a further improvement of an embodiment of the present invention, the "sending the warning time t1 to the user" specifically includes:
and calculating the users with priority reminding according to the related information of the users and different weights of different related information, and sending the early warning time t1 to the users with priority reminding.
As a further improvement of an embodiment of the present invention, the "calculating a user with a priority reminder according to the related information of a plurality of users and different weights of different related information" specifically includes:
the related information comprises the age, the role, the health degree and the distance from a kitchen of the user, and the total weight of each user is calculated according to the related information of each user;
and taking the user with the total weight ranked N as the user with the priority reminding.
As a further improvement of an embodiment of the present invention, the "calculating a total weight of each user according to the relevant information of each user" specifically includes:
acquiring the actual age a, the role r, the body strength b and the distance l from the kitchen of each user;
selecting a corresponding age weight Wa according to the age a, wherein if a < ═ 30, the Wa is weighted more greatly as a is larger, and otherwise, the Wa is weighted less as a is smaller;
selecting different role weights Wr according to different roles r, wherein the order of the role weights from big to small is as follows: father, mother, son or daughter, housekeeper or nanny, security or property;
selecting different body health degree weights Wb according to different body health degrees b, wherein the sequencing of the body health degree weights from large to small sequentially comprises the following steps: healthy, normal, thin, sick, disabled;
selecting a corresponding distance weight Wl according to the distance l from the kitchen, wherein the larger l is, the smaller Wl is;
the total weight W of each user is equal to the sum of the age weight Wa, the role weight Wr, the physical fitness weight Wb and the distance weight Wl corresponding to each user, i.e., W ═ Wa + Wr + Wb + Wl.
As a further improvement of an embodiment of the present invention, the method further comprises:
when the gas concentration Ct reaches an early warning value Ct1, sending a signal for closing a gas main switch to a gas emergency closing device, and sending a starting signal to a ventilation device of a kitchen;
and calculating the user with the priority reminding according to the related information of the plurality of users and different weights of different related information, and sending reminding information to the user with the priority reminding.
As a further improvement of an embodiment of the present invention, the method further comprises:
and after a signal for closing the gas main switch is sent to the gas emergency closing device, if the gas concentration of the user is detected to be continuously increased, an alarm is sent to the user with the priority prompt.
As a further improvement of an embodiment of the present invention, the method further comprises:
after the preset time length of a signal for closing the gas main switch is sent to the gas emergency closing device, if the gas concentration is detected to be reduced, a linear regression equation of the gas concentration reduction is obtained according to gas concentration reduction data in the preset time length, the time t2 when the gas concentration is recovered to a preset lower limit value Ct0 is calculated, and the t2 is sent to the user with the priority reminding.
In order to achieve one of the above objects, an embodiment of the present invention provides an electronic device, which includes a memory and a processor, wherein the memory stores a computer program operable on the processor, and the processor implements the steps of any one of the methods for predicting gas concentration in a refrigerator when executing the program.
In order to achieve one of the above objects, an embodiment of the present invention provides a refrigerator, which includes the electronic device.
Compared with the prior art, the method for predicting the gas concentration of the refrigerator obtains the gas concentration rising data in the preset time period after the gas is determined to start to leak, obtains the linear regression equation of the gas concentration rising, accordingly realizes prediction of the predicted gas concentration, sends related prediction information to a user, prevents further leakage of the gas concentration, and reduces harm of the gas to a human body.
Drawings
FIG. 1 is a schematic flow chart of a method for predicting gas concentration in a refrigerator according to the present invention.
Detailed Description
The present invention will be described in detail below with reference to specific embodiments shown in the drawings. These embodiments are not intended to limit the present invention, and structural, methodological, or functional changes made by those skilled in the art according to these embodiments are included in the scope of the present invention.
The invention provides a method for predicting gas concentration of a refrigerator, which is characterized in that after gas leakage is determined, gas concentration rising data in a preset time period is obtained, and a linear regression equation of the gas concentration rising is obtained, so that the prediction of the predicted gas concentration is realized, relevant prediction information is sent to a user, further leakage of the gas concentration is prevented, and the harm of the gas to a human body is reduced. The method comprises the following steps:
step S100: and (5) obtaining the gas concentration Ct of the kitchen.
The refrigerator is provided with a sensor which can detect the gas concentration Ct of the kitchen where the refrigerator is located.
Step S200: when the gas concentration Ct of the kitchen reaches a preset lower limit value Ct0, a linear regression equation Ct of the gas concentration rise is obtained according to the rise data of the gas concentration Ct in a preset time period.
Historical gas concentration data of a normal period and a gas leakage period are obtained, a preset lower limit value Ct0 of the gas concentration is determined, the Ct0 has no influence on a human body, and the gas is indicated to be out of a normal range and has been leaked.
As can be seen from the data of the historical gas leakage, the gas concentration rises and falls in a substantially linear manner, so that the rising data C1-Cn of the N gas concentrations in the predetermined time period are uniformly acquired, wherein the uniform acquisition refers to the same acquisition time interval between the gas concentrations, for example, one data per minute. The regression parameter w is then calculated:
and substituting the C1-Cn and w into the linear regression equation to obtain an initial value b of the coal gas concentration. That is, n values of b can be obtained by the acquisition time of C1 to Cn, C1 to Cn and the value of w, and then the average value is the final value of b. Note that the initial gas concentration value b is the historical gas concentration in the normal period.
Step S300: and calculating the early warning time t1 when the gas concentration reaches the early warning value Ct1 according to the linear regression equation and the time t0 when the gas concentration reaches the lower limit value Ct0, and sending the early warning time t1 to a user.
The early warning value Ct1 is a gas concentration value which causes slight damage to human bodies. Calculating the early warning time t1 when the gas concentration reaches an early warning value Ct1 according to a linear regression equation Ct ═ w × t + b:
t1＝(Ct1-Ct0)/w+t0。
and then sending the early warning time t1 to the user to remind the user that the gas concentration of the kitchen will reach the early warning value Ct1 at the time t 1. The user can prepare for treatment according to the information.
In a preferred embodiment, the "sending the warning time t1 to the user" specifically includes:
and calculating the users with priority reminding according to the related information of the users and different weights of different related information, and sending the early warning time t1 to the users with priority reminding.
Further, the "calculating the user with priority reminder according to the related information of the plurality of users and different weights of different related information" includes: the related information comprises the age, the role, the body health degree and the distance from the kitchen of the user, the total weight of each user is calculated according to the related information of each user, and the user with the total weight ranked N before is used as the user with priority reminding.
Wherein, the "calculating the total weight of each user according to the related information of each user" specifically includes:
acquiring the actual age a, the role r, the body strength b and the distance l from the kitchen of each user;
and selecting a corresponding age weight Wa according to the age a, wherein if a < ═ 30, the Wa is weighted more greatly if a is larger, and otherwise, the Wa is weighted less if a is smaller. Each age group may be given a weight, and the corresponding weight may be selected according to the age group in which the specific age falls.
Selecting different role weights Wr according to different roles r, wherein the order of the role weights from big to small is as follows: father, mother, son or daughter, housekeeper or nanny, security or property.
Selecting different body health degree weights Wb according to different body health degrees b, wherein the sequencing of the body health degree weights from large to small sequentially comprises the following steps: healthy, normal, thin and small, sick and disabled.
According to the distance l from the kitchen, selecting a corresponding distance weight Wl, wherein the larger l is, the smaller Wl is. The distance l may also be segmented, a weight is set for each paragraph, and a corresponding distance weight is selected according to the distance paragraph in which the specific distance l falls.
The total weight W of each user is equal to the sum of the age weight Wa, the role weight Wr, the physical fitness weight Wb and the distance weight Wl corresponding to each user, i.e., W ═ Wa + Wr + Wb + Wl.
Further, the "acquiring the actual age a, the character r, the body strength b and the distance l from the kitchen of each user" specifically includes:
calculating the age a of each user according to the input time and the current time by inputting the age for each user in advance;
obtaining the actual role r and the physical health degree b of each user through the role and the physical health condition input for each user in advance;
and acquiring the distance l between the user and the kitchen through a pre-bound positioning terminal.
If the user does not receive the early warning time t1 or receives the early warning time but does not go for processing, the refrigerator is required to control the gas concentration. Thus, in a preferred embodiment, the method further comprises:
firstly, when the gas concentration Ct is detected to reach the early warning value Ct1, a signal for closing a gas main switch is sent to a gas emergency closing device, and a starting signal is sent to a ventilation device of a kitchen.
The gas main switch is closed to control the rising of the gas concentration, and the ventilation device is opened to dredge the gas in the kitchen, reduce the gas concentration and prevent the irretrievable loss caused by the further rising of the gas concentration.
And then, according to the related information of the plurality of users and different weights of different related information, calculating the user with priority reminding, and sending reminding information to the user with priority reminding.
The reminding information comprises: the gas concentration has reached the pre-warning value Ct1 and signals the closing of the gas master switch and the activation of the ventilation means.
Further, the method further comprises:
after the preset time length of a signal for closing the gas main switch is sent to the gas emergency closing device, if the gas concentration is detected to be reduced, a linear regression equation of the gas concentration reduction is obtained according to gas concentration reduction data in the preset time length, the time t2 when the gas concentration is recovered to a preset lower limit value Ct0 is calculated, and the t2 is sent to the user with the priority reminding.
The user receives t2 above, i.e., knows when it is safe to enter the kitchen.
It should be noted that, since the gas main switch may fail to be turned off, in order to remind the user of a careful treatment, the method further includes:
and after a signal for closing the gas main switch is sent to the gas emergency closing device, if the gas concentration of the user is detected to be continuously increased, an alarm is sent to the user with the priority prompt.
The alarm is used for reminding a user that the gas main switch fails to be closed, the gas concentration is further increased, and the user needs to make a countermeasure.
In a specific embodiment, the refrigerator detects the gas concentration Ct of the kitchen where the refrigerator is located in real time through a sensor. And then determining a preset lower limit value Ct0 of the gas concentration by acquiring historical gas concentration data of the normal period and the gas leakage period. When the gas concentration Ct of the kitchen reaches a preset lower limit value Ct0, a linear regression equation Ct of the gas concentration rise is obtained according to the rise data of the gas concentration Ct in a preset time period. And calculating the early warning time t1 when the gas concentration reaches the early warning value Ct1 according to the linear regression equation and the time t0 when the gas concentration reaches the lower limit value Ct0, and sending the early warning time t1 to a user.
The invention also provides an electronic device, which comprises a memory and a processor, wherein the memory stores a computer program capable of running on the processor, and the processor implements any one of the steps of the method for predicting gas concentration of the refrigerator when executing the program, namely implements the steps of any one of the technical schemes of the method for predicting gas concentration of the refrigerator.
The invention also provides a refrigerator comprising the electronic device.
It should be understood that although the present description refers to embodiments, not every embodiment contains only a single technical solution, and such description is for clarity only, and those skilled in the art should make the description as a whole, and the technical solutions in the embodiments can also be combined appropriately to form other embodiments understood by those skilled in the art.
The above-listed detailed description is only a specific description of a possible embodiment of the present invention, and they are not intended to limit the scope of the present invention, and equivalent embodiments or modifications made without departing from the technical spirit of the present invention should be included in the scope of the present invention.
Claims (10)
1. A method for predicting gas concentration of a refrigerator is characterized by comprising the following steps:
acquiring the gas concentration Ct of a kitchen;
when the gas concentration Ct of the kitchen reaches a preset lower limit value Ct0, obtaining a linear regression equation Ct ═ w t + b of the gas concentration rise according to the gas concentration rise data of the Ct in a preset time period;
and calculating the early warning time t1 when the gas concentration reaches the early warning value Ct1 according to the linear regression equation and the time t0 when the gas concentration reaches the lower limit value Ct0, and sending the early warning time t1 to a user.
2. The method for predicting the gas concentration of the refrigerator according to claim 1, wherein the obtaining a linear regression equation Ct ═ w × t + b "according to the rising data of the gas concentration Ct in the predetermined time period specifically comprises:
uniformly acquiring N rising data C1-Cn of the gas concentration in the preset time period;
calculating a regression parameter w:
and substituting the C1-Cn and w into the linear regression equation to obtain an initial value b of the coal gas concentration.
3. The method for predicting the gas concentration in the refrigerator according to claim 1, wherein the step of sending the warning time t1 to the user specifically comprises the steps of:
and calculating the users with priority reminding according to the related information of the users and different weights of different related information, and sending the early warning time t1 to the users with priority reminding.
4. The method for predicting the gas concentration by using the refrigerator as claimed in claim 3, wherein the step of calculating the user with the priority prompt according to the related information of the users and different weights of the related information specifically comprises the following steps:
the related information comprises the age, the role, the health degree and the distance from a kitchen of the user, and the total weight of each user is calculated according to the related information of each user;
and taking the user with the total weight ranked N as the user with the priority reminding.
5. The method for detecting gas concentration by using a refrigerator as claimed in claim 4, wherein the step of calculating the total weight of each user according to the related information of each user specifically comprises the steps of:
acquiring the actual age a, the role r, the body strength b and the distance l from the kitchen of each user;
selecting a corresponding age weight Wa according to the age a, wherein if a < ═ 30, the Wa is weighted more greatly as a is larger, and otherwise, the Wa is weighted less as a is smaller;
selecting different role weights Wr according to different roles r, wherein the order of the role weights from big to small is as follows: father, mother, son or daughter, housekeeper or nanny, security or property;
selecting different body health degree weights Wb according to different body health degrees b, wherein the sequencing of the body health degree weights from large to small sequentially comprises the following steps: healthy, normal, thin, sick, disabled;
selecting a corresponding distance weight Wl according to the distance l from the kitchen, wherein the larger l is, the smaller Wl is;
the total weight W of each user is equal to the sum of the age weight Wa, the role weight Wr, the physical fitness weight Wb and the distance weight Wl corresponding to each user, i.e., W ═ Wa + Wr + Wb + Wl.
6. The method for predicting gas concentration of a refrigerator according to claim 1, further comprising:
when the gas concentration Ct reaches an early warning value Ct1, sending a signal for closing a gas main switch to a gas emergency closing device, and sending a starting signal to a ventilation device of a kitchen;
and calculating the user with the priority reminding according to the related information of the plurality of users and different weights of different related information, and sending reminding information to the user with the priority reminding.
7. The method for predicting the gas concentration of the refrigerator as claimed in claim 6, wherein the method further comprises:
and after a signal for closing the gas main switch is sent to the gas emergency closing device, if the gas concentration of the user is detected to be continuously increased, an alarm is sent to the user with the priority prompt.
8. The method for predicting the gas concentration of the refrigerator as claimed in claim 6, wherein the method further comprises:
after the preset time length of a signal for closing the gas main switch is sent to the gas emergency closing device, if the gas concentration is detected to be reduced, a linear regression equation of the gas concentration reduction is obtained according to gas concentration reduction data in the preset time length, the time t2 when the gas concentration is recovered to a preset lower limit value Ct0 is calculated, and the t2 is sent to the user with the priority reminding.
9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program operable on the processor, and wherein the processor executes the program to implement the steps of the method for predicting gas concentration in a refrigerator according to any one of claims 1 to 8.
10. A refrigerator characterized in that it comprises an electronic device according to claim 9.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010475560.8A CN113743638A (en) | 2020-05-29 | 2020-05-29 | Method and equipment for predicting gas concentration of refrigerator and refrigerator |
| PCT/CN2021/096416 WO2021213545A1 (en) | 2020-05-29 | 2021-05-27 | Method and device for predicting gas concentration by means of refrigerator, and refrigerator |
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| CN202010475560.8A CN113743638A (en) | 2020-05-29 | 2020-05-29 | Method and equipment for predicting gas concentration of refrigerator and refrigerator |
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN203810840U (en) * | 2013-12-09 | 2014-09-03 | 南京创维家用电器有限公司 | Refrigerator with gas leakage detection function |
| CN105486807A (en) * | 2015-11-25 | 2016-04-13 | 南京缔尔达智能科技有限公司 | Method for analyzing hidden safety trouble of dangerous chemical gas |
| CN205880534U (en) * | 2016-07-15 | 2017-01-11 | 四川建筑职业技术学院 | Intelligent home control system |
Family Cites Families (6)
| Publication number | Priority date | Publication date | Assignee | Title |
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| US10460347B2 (en) * | 2012-12-30 | 2019-10-29 | Certona Corporation | Extracting predictive segments from sampled data |
| CN103208168B (en) * | 2013-01-31 | 2016-05-25 | 杨如祥 | Coal gas monitoring alarm method |
| US20180136184A1 (en) * | 2016-11-17 | 2018-05-17 | Li-Cor, Inc. | Rapid response curves and survey measurements |
| CN106874671B (en) * | 2017-02-15 | 2019-11-19 | 淄博祥龙测控技术有限公司 | A method of the data-driven for spontaneous fire in coal mine big data platform |
| CN107918998A (en) * | 2017-11-30 | 2018-04-17 | 孟笛 | A kind of Household fuel gas leakage monitoring and pre-warning system and method |
| CN110579001A (en) * | 2019-08-12 | 2019-12-17 | 安徽美博智能电器有限公司 | Control method and device of air conditioner |
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- 2020-05-29 CN CN202010475560.8A patent/CN113743638A/en active Pending
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- 2021-05-27 WO PCT/CN2021/096416 patent/WO2021213545A1/en active Application Filing
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN203810840U (en) * | 2013-12-09 | 2014-09-03 | 南京创维家用电器有限公司 | Refrigerator with gas leakage detection function |
| CN105486807A (en) * | 2015-11-25 | 2016-04-13 | 南京缔尔达智能科技有限公司 | Method for analyzing hidden safety trouble of dangerous chemical gas |
| CN205880534U (en) * | 2016-07-15 | 2017-01-11 | 四川建筑职业技术学院 | Intelligent home control system |
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